Superforecasters tend to believe x-risk isn’t a big deal. Regardless of whether they’re using reasonable procedures, they’re getting the wrong object-level answer in this case. FRI’s consulting plausibly made the scaling policies worse. Hard to say without knowing more details.
(I’m thinking particular of XPT, which is from 2023 so it may be outdated at this point. But that tournament had superforecasters predicting only a 1% chance of AI extinction, which is ludicrous and should not be used as the basis for decisions.)
Sharing what context I’m able to: Our work in this space so far has mostly been around assessing both risks and effective safeguards for AI-biorisk and AI-cybersecurity risk.
Superforecasters and domain experts tend to be relatively aligned on these topics so far (e.g., see this study as one example, and a later update here). (We’ve completed private research on AI-cybersecurity risk and will be publishing some of it soon.)
Superforecasters tend to believe x-risk isn’t a big deal. Regardless of whether they’re using reasonable procedures, they’re getting the wrong object-level answer in this case. FRI’s consulting plausibly made the scaling policies worse. Hard to say without knowing more details.
(I’m thinking particular of XPT, which is from 2023 so it may be outdated at this point. But that tournament had superforecasters predicting only a 1% chance of AI extinction, which is ludicrous and should not be used as the basis for decisions.)
Sharing what context I’m able to: Our work in this space so far has mostly been around assessing both risks and effective safeguards for AI-biorisk and AI-cybersecurity risk.
Superforecasters and domain experts tend to be relatively aligned on these topics so far (e.g., see this study as one example, and a later update here). (We’ve completed private research on AI-cybersecurity risk and will be publishing some of it soon.)